Acoustic signal detection systems (also known as sonar, ultrasound, etc. systems) see application in many environments, e.g., medical, underwater targeting systems, robotic control, etc. At least two generations of acoustic signal sensing system precede this invention. The first generation employed single transducers and each sensor extracted time-of-flight of an emitted signal by threshold detection to locate a nearest obstacle lying along a particular direction. Multiple objects were detected and maps were generated by either rotating a single transducer or employing a ring of transducers operating separately. Such systems can be found described in "Sonar-Based Real World Mapping And Navigation", Elfes, IEEE Transactions On Robotics Automation, pages 249-265, 1987; and "The Sonar Ring: Obstacle Detection For A Mobile Robot" Walter Proceedings IEEE International Conference On Robotics Automation, pages 1574-1578, Raleigh, N.C., Mar. 31-Apr. 3, 1987.
A second generation of acoustic detection systems employed transducer arrays which consisted of two or more sensors. Such arrays processed echoes from a single emission to classify simple objects such as planes, corners and edges in terms of their echo characteristics. Such arrays allowed the identification and location of multiple objects from one location. Maps of identifiable features were generated by moving or rotating the array, however, the configuration of the array was fixed during operation. Such systems can be found described in the following references:
R. Kuc and Y. D. Di. Intelligent Sensor Approach To Differentiating Sonar Reflections From Corners and Planes. L. O. Hertzberger, editor, Intelligent Autonomous Systems, pages 329-333. Elsevier, Amsterdam, 1986. PA0 B. Barshan and R. Kuc. Differentiating Sonar Reflections From Corners and Planes by Employing an Intelligent Sensor. IEEE Trans. Pattern Anal. Machine Intell., 12960:560-569, 1990. PA0 H. Peremans, K. Audenaert and J. M. Van Campenhout. A High-Resolution Sensor Based on Tri-Aural Perception. IEEE Trans. Robotics Automation, 9(1)L36-48, 1993. PA0 A. Sabatini. Active Hearing for External Imaging Based on an Ultrasonic Transducer Array. Proceedings IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pages 829-836, 1992. PA0 Y. Nagashima and S. Yuta. Ultrasonic Sensing For a Mobile Robot to Recognize an Environment--Measuring the Normal Direction to Walls. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pages 805-812, Raleigh, N.C., July, 1992.
For successful recognition of an object in an acoustic signal environment, the mechanism by which the features of an object produce echoes should be understood. The main echo producing mechanism is the abrupt change in cross-sectional area of an object that is exposed to an incident wave form. Such an abrupt change manifests itself in large specular echoes that are commonly observed in conventional sonar systems. However, smaller diffracted echoes are also produced by abrupt changes in the derivatives of the cross-sectional area of the object.
Using such echo information, attempts have been made to identify members of a given set of simple objects. The results were disappointing because observed differences in the echoes from a given object, located at different angles of the integrating beam, were as great as differences in echoes from different objects. See Sasaki et al. "Classification of Objects' Surface by Acoustic Transfer Function" Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 821-828, 1992.
To improve acoustic recognition of objects, template matching has been performed. To generate a set of templates, echoes from an object are observed at a number of receivers and are collected so that a template can be associated with each set of locations and stable orientations of an object. Templates enable a system to identify, locate and determine an object's orientation by associating received echoes with the stored templates that match the echo most closely (in a least-square error sense). In prior art reporting this finding, sensor placement was performed heuristically (see Richardson et al., "Acoustic Recognition of Objects in Robotics: Determination of Type, Pose, Position and Orientation", Acoustic Imaging, Vol. 16, pages 613-620, Plenum Press, NY, N.Y., 1988).
In order for template recognition to be effective, the number of templates must not be too large. As noted by Sasaki et al. above, the echo waveform changes significantly as the object location varies within the beam pattern. For recognition, a template must be available for every possible object location, resulting in an impractically large number of templates. The system incorporating the invention hereof and described below orients the object at a known location relative to the beam pattern of the transmitter and receivers. This known orientation "standardizes" the echo pattern received from an object and thus reduces the number of templates, making object recognition feasible.
Object recognition using acoustic signals evidences a number of problems when two or more sensors are employed. The first problem is termed "correspondence" and is manifested by an uncertainty at the receivers as to which echoes received by one receiver are to be paired with echoes appearing in another receiver. A second problem is termed "virtual" objects, wherein a multi-receiver system is confronted with objects which lie at approximately a same range within an echo producing region. Under such a condition, an acoustic sensing system derives an azimuth for the objects, which azimuth is aimed at a virtual object located somewhere between the two actual objects. In this case, since the azimuth does not point at a real object, the echoes received are different from those expected. This difference is exploited by the invention hereof to recognize the occurrence of virtual objects and as a means of directing the system so that it detects only actual objects.
It is known that certain mammals employ echo location for prey capture by emitting a series of acoustic pulses and processing the echoes. Both bats and dolphins employ such echo location modalities. Bat echo location systems are known to be especially effective in moderately open environments. Bats are known to turn their ears in the direction of a sound source and to move to observe an object from a different direction so as to enable a more precise determination of its identity.
Accordingly, it is an object of this invention to provide an improved acoustic sensing system which employs a target discrimination modality similar to that found in a biological system.
It is another object of this invention to provide an improved acoustic target detection system that is adaptive to altered target locations and ranges.
It is yet another object of this invention to provide an improved acoustic object detection system that is particularly adapted to use in robotic environments.